My my.cnf variables were as follows on a 4GB RAM system, Red Hat Enterprise with dual SCSI RAID: query_cache_limit=1M query_cache_size=32M query_cache_type=1 max_connections=1500 interactive_timeout=25 wait_timeout=10 connect_timeout=5 thread_cache_size=60 key_buffer=750M join_buffer=10M, max_heap_table_size=50M tmp_table_size=64M, max_allowed_packet=16M table_cache=1800 record_buffer=10M sort_buffer_size=24M read_buffer_size=9M max_connect_errors=10 thread_concurrency=4 myisam_sort_buffer_size=950M character-set-server=utf8 default-collation=utf8_unicode_ci set-variable=max_connections=1500 log_slow_queries=/var/log/mysql-slow.log sql-mode=TRADITIONAL concurrent_insert=2 low_priority_updates=1. For example, if you have a star join with dimension tables being small, it would not slow things down too much. Try to avoid it. Instead, you must refer to the mysql.general_log and mysql.slow_log tables on your database to view the log data. is there some sort of rule of thumb here.. use a index when you expect your queries to only return X% of data back? Learn more about Percona Server for MySQL. It used to take about 9 hours to insert all the files, and now it takes upwards of 15 hours, which is becoming a problem. Try minimizing the number of indexes while running a big process like this one, then reapplying the indexes afterward. I wonder how I can optimize my table. Hope this helps. I received a Tweet earlier this week which pointed out that LIMIT is slow when dealing with large offsets so take a look at this here. So give your Anaconda small pieces of meat than full deer all in once. Tip 4: Take Advantage of MySQL Full-Text Searches Probably, the server is reaching I/O limits… I played with some buffer sizes but this has not solved the problem.. Has anyone experience with table size this large ? It depends on your searches. We will have to do this check in the application. Some people would also remember if indexes are helpful or not depends on index selectivity – how large the proportion of rows match to a particular index value or range. table meant for searching data could contain duplicate columns than the table meant for viewing the selected data. We do a “VACCUM” every *month* or so and we’re fine. 2.5-3 mins to invoke the same query used in SETUP A. SPECS of SETUP B: OS: Red Hat Linux 4 Memory: 512MB. Also have two myisam tables: One with 5 million records using 1.2 GB of Set slow_query_log_file to the path where you want to save the file. By this post I try to divide into smaller table and running one sql per time, but still not faster. Is it better to have: INDEX (‘col1′,’col2′,’col3’); or: INDEX1 (‘col1’), INDEX2 (‘col2’), INDEX3 (‘col3’) ?! You can think of it as a webmail service like google mail, yahoo or hotmail. Here is the information: show create table snpmarker; [ code ] snpmarker | CREATE TABLE `snpmarker` ( `markerid` int(11) NOT NULL auto_increment, `animalid` int(11) NOT NULL, `locusid` int(11 That’s why I’m now thinking about useful possibilities of designing the message table and about whats the best solution for the future. You see a row for each table that was involved in the query: The important pieces here are the table name, the key used, and the number of rows scanned during the execution of the query. Ever wonder how to log slow queries to a MySQL table and set an expire time? “fit your data into memory” in a database context means “have a big enough buffer pool to have the table/db fit completely in RAM”. > > > -- … A FULLTEXT indexes have an inverted index design. It was very slow and the process that ran on another machine that took 1 hour this is 6 hours. So rank 1 through to rank 500,000. Your table is not large by any means. Mainly because it gets huge, spikes disk I/O and it’s not as easy to read as logging to a MySQL table. I don’t want to use split the database. You also need to consider how wide are rows – dealing with 10 byte rows is much faster than 1000 byte rows. I get the keyword string then look up the id. Additionally, a 404 Not Found error was encountered while trying to use an ErrorDocument to handle the request. The table contains 36 million rows (Data size 5GB, Index size 4GB). First insertion takes 10 seconds, next takes 13 seconds, 15, 18, 20, 23, 25, 27 etc. Could it, for example, help to increase “key_buffer_size”? It can easily hurt overall system performance – by trashing OS disk cache, and if we compare table scan on data cached by OS and index scan on keys cached by MySQL, table scan uses more CPU (because of syscall overhead and possible context switches due to syscalls). For example, if a table with 30 million records and a composite key on userID, Could one expect better performance by splitting into 30 tables of 1 million records each, or are composite keys that efficient? As you could see in the article in the test I’ve created range covering 1% of table was 6 times slower than full table scan… which means at about 0.2% table scan is preferable. What change you’re speaking about ? The ‘data’ attribute contents the binary fragments. Get the highlights in your inbox every week. I guess the rest of the presentation is spend on other 101 items like functions triggering full table scans and interger keys are faster than string ids. I have a very large table, 3 billion rows, 300GB in size. I’ve read SHE-DBA’s blog on using MySQL as a data-warehousing platform and where it _can_ be used as such provided the design is good and the queries are optimised. I don’t know why this happens and if any one also had this problem. So only add indexes that actually increase read performance. As an example, I've got a process that merges a 6 million row table with a 300 million row table on a daily basis. In the end I changed the SQL…as suggested. What could be the reason? By logging to a table not only is it stored nice and neat, but you can also set how long to keep the records for. the type of DB you are using for the job can be a huge contributing factor for example Innodb vs MyISAM. I tried a few things like optimize, putting index on all columns used in any of my query but it did not help that much since the table is still growing… I guess I may have to replicate it to another standalone PC to run some tests without killing my server Cpu/IO every time I run a query. My queries are complex and involves a quite a few joins (due to the normalisation) and multiple subqueries (due to nature of the data). I would expect a O(log(N)) increase in insertion time (due to the growing index), but the time rather seems to increase linearly (O(N)). Storing the table in memory does have some implications. 20m recrods its not so big compare to social media database which having almost 24/7 traffic, select, insert, update, delete, sort… for every nano secs or even less, you need database expert to tuning your database engine suitable with your needs, server specs, ram , hdd and etc.. In theory optimizer should know and select it automatically. Sorry for the confusion, but this is what I was talking about also. Indexes help speed up the look up phase of a record(s). PostgreSQL solved it for us. adding columns, changing column names, etc.) SELECT TITLE FROM GRID WHERE STRING = ‘sport’; When I run the query below, it only takes 0.1 seconds : SELECT COUNT(*) FROM GRID WHERE STRING = ‘sport’; So while the where-clause is the same, the first query takes much more time. 300MB table is tiny. InnoDB is suggested as an alternative. I may add that this one table had 3 million rows, and growing pretty slowly given the insert rate. In real DBs like PG, you can set an index on the count too, as well as several “partial indexes”. Also, are there any suggestions about which storage engine to use? The site and the ads load very slowly. We’re using LAMP. As we saw my 30mil rows (12GB) table was scanned in less than 5 minutes. I’m writing about working with large data sets, these are then your tables and your working set do not fit in memory. But, would this (nearly full table joins within a script that runs frequently) be a case were it’d be better to store a small amount of data from table B (the “many”; five or six items; thresholds for notifications actually) as *serialized* data within Table A? Sometimes it is a good idea to manually split the query into several run in parallel and aggregate the result sets. However, with ndbcluster the exact same inserts are taking more than 15 min. If it is possible you instantly will have half of the problems solved. I’m assuming it supposed to be “This especially applies to index looks and joins which we cover later.”. MySQL database really slow with a really big table [closed] Ask Question Asked 6 years, 6 months ago Active 5 years, 11 months ago Viewed 8k times 1 2 Closed. This query takes about 45 minutes to execute (DELETE FROM Data WHERE Cat=’1021′ AND LastModified, I am having a problem when I try to “prune” old data. 4 million rows), the execution time is more or less 30 seconds. This doesn't mean that you should add indexes everywhere because each index makes it longer to write to the database. The engine is InnoDB. The question I have, is why is this happening, and if there is any kind of query I can preform in order to “focus” the DBMS “attention” to the particular table (in context), since SELECTing data is always faster then INSERTing it. I tried SQL_BIG_RESULT, analyze table, etc… nothing seems to help. You need a lot of work on your technical writing skills. Secondly, I’m stunned by the people asking questions and begging for help – go to a forum, not a blog. This did not seem to speed it up any. SPECS of SETUP A: OS: Windows XP Prof Memory: 512MB. Sergey, Would you mind posting your case on our forums instead at http://forum.mysqlperformanceblog.com and I’ll reply where. To use it, open the my.cnf file and set the slow_query_log variable to "On." – what parameters i need to insert manually in my.cnf for best performance & low disk usage? Mysql will only use one > index for a table per query. The load took some 3 hours before I aborted it finding out it was just about 20% done. Even storage engines have very important differences which can affect performance dramatically. A count will always take more. But whenever I run this query in my application on ADODB connection, it was tooking 8-10 seconds. This query works “fine”…some seconds to perform. Percona's experts can maximize your application performance with our open source database support, managed services or consulting. in a manner that the table size remain in a good range for fast queries. I could send the table structures and queries/ php cocde that tends to bog down. – may i remove old_passwords=1 & big-tables? MySQL indexes may take up more space and decrease performance on inserts, deletes, and updates. -Thanks, Jitendra, If I need time difference calculation on the same datetime field between 4 types of events related to the same thing (i.e books), and yearly the number of this events goes up to 2 million, what is better: A) 1 big table with correctly indexed book_id and event_id and possible partitioning by book type (up to 50 types) B) 4 tables, one for each event, indexed with the same foreign key that holds the relation and possible partitioning all 4 tables by the book type. Sorry for mentioning this on a mysql performance blog. SETUP A: We have a web application that uses MS SQL database. MySQL has a built-in slow query log. To include queries that do not use indexes for row lookups in the statements written to the slow query log, enable the … MYISAM table with the following activity: 1. You are responsible for ensuring that you have the necessary permission to reuse any work on this site. PARTITION tables? Just do not forget EXPLAIN for your queries and if you have php to load it up with some “random” data which is silimar to yours that would be great. And this is when you can’t get 99.99% keycache hit rate. Is there something special about a delete that makes it MUCH MUCH slower than a select? OPTIMIZE helps for certain problems – ie it sorts indexes themselves and removers row fragmentation (all for MYISAM tables). Could the INSERTs be slow, dued to the size of the PRIMARY KEY?! Speaking about “open_file_limit” which limits number of files MySQL can use at the same time – on modern operation systems it is safe to set it to rather high values. [mysqld] ... key_buffer = 512M max_allowed_packet = 8M table_cache = 512 sort_buffer_size = 32M read_buffer_size = 32M read_rnd_buffer_size = 128M myisam_sort_buffer_size = 256M thread_cache = 32 query_cache_size = 256M. – do i switch table from MyISAM to InnoDB (if yes, how to configure InnoDB for best performance?). ), i also have problems with my queries i tried to optimized mysql using the explain and i got 1 row result per table except the master table in which it has 13,000 records. 11. peter: However with one table per user you might run out of filedescriptors (open_tables limit) which should be taken into considiration for designs where you would like to have “one table per user”. (In terms of Software and hardware configuration). or just If your Access database running slow over network then try this method. There are two main output tables that most of the querying will be done on. You can tweak memory usage in your ini file or add memory or processors to your computer. When these 100 albums are scanned, associated pictures are pinpointed using the album_id key. Has the JOIN thing gone completely crazy??? first 2Lacks records are getting fast after that it is taking lot off time to fetch and fetching some 100 records only very slow. As you probably seen from the article my first advice is to try to get your data to fit in cache. The initial table (unit) was 100K rows. One more hint if you have all your ranges by specific key ALTER TABLE … ORDER BY key would help a lot. This article is not about MySQL being slow at large tables. i think max rows per table should be 50-100k rows, Hi All, Can any one please help me how to solve performance issue in mysql database. The difference in USE INDEX And FORCE INDEX comes from (Quote from MySQL documentation): The FORCE INDEX hint acts like USE INDEX (index_list), with the addition that a table … ALTER TABLE normally rebuilds indexes by sort, so does LOAD DATA INFILE (Assuming we’re speaking about MyISAM table) so such difference is quite unexpected. id select_type table type possible_keys key key_len ref rows Extra 1 SIMPLE stat range dateline dateline 4 NULL 277483 Using where; Using temporary; Using filesort 1 SIMPLE iplist eq_ref PRIMARY PRIMARY 4 vb38.stat.ip_interval 1. –> Processed data to the users PC pull from server(select a,b,c from table) -> process data at users PC (due to increase in computational power of current PC) (select a, join b, where c…). All it does is process these logs, and handle the occasional query we need to do when we run a report for someone, maybe once a week. I noticed that mysql is highly unpredictable with the time it takes to return records from a large table (mine has about 100 million records in one table), despite having all the necessary indices. Since this is a predominantly SELECTed table, I went for MYISAM. If you need to search on col1, col2, col3 then create an index(col1,col2,col3). I implemented a simple logging of all my web sites access to make some statistics (sites access per day, ip address, search engine source, search queries, user text entries, …) but most of my queries went way too slow to be of any use last year. How random accesses would be to retrieve the rows. I was having indexes almost the size of the complete table (+/- 5GB), which made the whole table around 10GB. Select query on this table runs very slow tooks around 60 to 70 sec One observation is only following select query runs fast Select ID, MAsterTable1_ID from test_data where MAsterTable1_ID='something' Explain output shows or just when you have a large change in your data distribution in your table? It took approx. I guess this is due to index maintenance. The three main issues you should be concerned if you’re dealing with very large data sets are Buffers, Indexes, and Joins. Could you please advise me. I hope this helps. In such cases commercial services work much better https://www.percona.com/contact/sales/, I am using mysql query select contentid,SheetName,languageName from contentapplicationview where sheetName in (select tblapplicationauthorized.date from tblapplicationauthorized where applicationid='” + applicationId + “‘ and authscrname='” + screenName + “‘) and fkApplicationId='”+applicationId+”‘ order by SheetName,languageName. Processing in memory is so much faster and you have whole bunch of problems solved just doing so. This measure is a precaution to reduce the possibility of a large log file either blocking database use or affecting performance. But, do you have any suggestions on how to circumvent them? Red Hat and the Red Hat logo are trademarks of Red Hat, Inc., registered in the United States and other countries. Now if your data is fully on disk (both data and index) you would need 2+ IOs to retrieve the row – which means you get about 100 rows/sec. Query Cache Configuration. Some operators will control the machines by varying the values in the plc board.We need to collect that values from those machines via wireless communication and store that values into the database server.We need to observe that ,the operator operating the machines correctly or not at server place.Here problem is how we have to create the database for dynamic data. i am using mysql I had a problem with joining table where all table had a records more than 2 lakhs so when I run it from my application. SETUP B: It was decided to use MYSql instead of MS SQL. In MySQL 5.1 there are tons of little changes. 1st one (which is used the most) is “SELECT COUNT(*) FROM z_chains_999”, the second, which should only be used a few times is “SELECT * FROM z_chains_999 ORDER BY endingpoint ASC”. My Max script execution time in PHP is set to 30 Secs. Hi All, I have the following issues: When I make joining on a table which have approx 10,00,00,00 records with other table which have approx 1,00,00,000 records, it takes more than two hours to give result. The problem I have, is regarding some specific tables in the database, which I use for a couple of months duration, minning them with detailed data of a particular task. old_passwords=1 big-tables, [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid, – i have webmin installed, but when I change mysql vars and restart server, my configs are not applied, defautl mysql. Runing explain is good idea. So you understand how much having data in memory changes things, here is a small example with numbers. I don't expect it to be really fast but is it normal to be that slow? Obviously, the resulting table becomes large (example: approx. So have you any idea how this query can be optimized further or it’s normal time for such query? Yes. Is there a way to optimize? That is operator can change his entire table of data (values) at any point of time. When invoking a SELECT statement in LogDetails table(having approx. The server has 4GB of RAM, dual Core 2 2.6GHz processors. page number 627500 http://www.ecommercelocal.com/pages.php?pi=627500 the site load very slow some time with error as below: The server encountered an internal error or misconfiguration and was unable to complete your request. the time for retrieving records between 1-20000, 20000-40000, … is quite stable (about 5 seconds for each range). One of the reasons elevating this problem in MySQL is a lack of advanced join methods at this point (the work is on a way) – MySQL can’t do hash join or sort-merge join – it only can do nested loops method, which requires a lot of index lookups which may be random. Eric. and the number of rows are also in the couple millions. loaded into large tables, total mysql data size is 96 gig, the large tables are 2-6 gig. In general without looking at your ini file and having no knowledge of your system it would be your indexes. I thus guess my database is not well configured for this kind of inserts at the moment (i.e. Great article and interesting viewpoints from everyone. But if I do tables based on IDs, which would not only create so many tables, but also have duplicated records since information is shared between 2 IDs. How should I create table structure so I can do rankings for each user based on their average score? 5.0.45 via socket on x86_64 centos 5.2, 1 CPU 4core with 4 Gb RAM, 3Tb SATA disk space Load avg: 0.81 (1 min) 0.68 (5 mins) 0.73 (15 mins) Real memory 3.86 GB total, 1.38 GB used Virtual memory 4 GB total, 288 kB used, I had a problem with COUNT(*) when I run it from my application. Turn on Logging to Find Poorly Performing Queries. Can Mysql lose index during high traffic load ? I’m thinking of doing a number of queries to SELECT subsets of data into smaller TEMPORARY TABLES then doing a JOIN on them. However, when it came to about 560000-580000 and above, the time became significant longer (more than 50 seconds). I have the following scenario: I have many (several 100K) lists that contain 50 items, each. Using 1 harddrive for the OS and APPs and a 2nd hardrive for the mysql data. It scans 2,000,000 pictures, then, for each picture, it scans 20,000 albums. Would duplicating data on inserts and updates be an option which would mean having two of the same table, one using InnoDB for main reading purposes and one for MyISAM for searching using Full text search and every time you do an update actually uipdate bith table etc.